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Latest revision as of 18:16, 2 October 2025
Technical Documentation: Server Hardware Inventory - High-Density Compute Node (HDCN-8000)
This document provides a comprehensive technical overview of the **High-Density Compute Node (HDCN-8000)** server configuration. This platform is engineered for demanding, scalable workloads requiring exceptional computational throughput and high-speed I/O capabilities.
1. Hardware Specifications
The HDCN-8000 is a 2U rack-mountable system built around a dual-socket motherboard architecture, optimized for processor density and high-speed memory access. All components adhere to enterprise-grade reliability standards (e.g., ECC support, hot-swappable drives).
1.1. Chassis and Platform
The foundation of the HDCN-8000 is a robust, airflow-optimized 2U chassis designed for dense rack deployments.
| Feature | Specification |
|---|---|
| Form Factor | 2U Rackmount |
| Motherboard Chipset | Dual-Socket Intel C741 Equivalent (Customized for High-Core Count) |
| Power Supply Units (PSUs) | 2x 2000W Redundant (1+1) Platinum Efficiency (92%+) |
| Cooling System | 6x Hot-Swappable High-Static Pressure Fans (N+1 Redundancy) |
| System Management | Integrated Baseboard Management Controller (BMC) supporting IPMI 2.0 and Redfish API |
| Expansion Slots | 4x PCIe 5.0 x16 Full-Height, Half-Length (FHFL) slots; 2x OCP 3.0 slots |
1.2. Central Processing Units (CPUs)
The configuration utilizes the latest generation of high-core-count processors, maximizing parallel processing capability.
| Parameter | Socket 1 Specification | Socket 2 Specification |
|---|---|---|
| Processor Model | Intel Xeon Scalable (Sapphire Rapids equivalent) Platinum 8592+ | Intel Xeon Scalable (Sapphire Rapids equivalent) Platinum 8592+ |
| Core Count (Physical) | 60 Cores | 60 Cores |
| Thread Count (Logical) | 120 Threads (Hyper-Threading Enabled) | 120 Threads (Hyper-Threading Enabled) |
| Base Clock Frequency | 1.9 GHz | 1.9 GHz |
| Max Turbo Frequency (Single Core) | Up to 3.8 GHz | Up to 3.8 GHz |
| L3 Cache (Total Per CPU) | 112.5 MB | 112.5 MB |
| TDP (Thermal Design Power) | 350W | 350W |
| Total System Core Count | 120 Cores / 240 Threads |
The use of Intel QuickAssist Technology (QAT) acceleration cores, integrated within the CPU package, is fully enabled for cryptographic and compression offload tasks.
1.3. Memory Subsystem
Memory capacity and bandwidth are critical for this high-density node, supporting large in-memory datasets and virtualization density.
| Parameter | Specification |
|---|---|
| Total Capacity | 2 TB (Terabytes) DDR5 Registered ECC RDIMM |
| Memory Speed | 4800 MT/s |
| Configuration | 32 DIMMs x 64 GB modules (16 DIMMs per CPU) |
| Memory Channels | 8 Channels per CPU (Total 16 Channels) |
| Memory Type | DDR5 ECC RDIMM (JEDEC Standard Compliant) |
| Maximum Supported Capacity (Theoretical) | 8 TB (Using 256 GB 3DS RDIMMs) |
The memory topology is configured for optimal interleaving across all 16 channels to ensure maximum effective bandwidth, crucial for NUMA balancing in multi-threaded applications.
1.4. Storage Configuration
The HDCN-8000 prioritizes high-speed, low-latency NVMe storage for primary operations, complemented by high-capacity SAS/SATA drives for bulk data.
1.4.1. Boot and Primary Storage (NVMe)
The system utilizes the onboard PCIe root complex directly connected to the storage controllers for maximum throughput.
| Bay Location | Quantity | Capacity (Per Drive) | Interface | Role |
|---|---|---|---|---|
| Front Bay (Hot-Swap) | 8x U.2/M.2 Slots | 7.68 TB | PCIe Gen 5.0 x4 | Operating System, Caching, and High-IO Databases |
1.4.2. Secondary Storage (Data Array)
Secondary storage is managed via an external Hardware RAID Controller for flexibility and scalability.
| Bay Location | Quantity | Capacity (Per Drive) | Interface | Role |
|---|---|---|---|---|
| Rear Bay (Hot-Swap) | 12x 3.5" Bays | 18 TB | SAS-4 (12 Gb/s) | Bulk Storage, Archives, Virtual Machine Images |
1.4.3. RAID Controller
The system incorporates a dedicated Host Bus Adapter (HBA) capable of RAID functionality.
- **Controller Model:** Broadcom MegaRAID 9680-8i (or equivalent)
- **Cache:** 4GB FBWC (Flash Backed Write Cache)
- **RAID Levels Supported:** 0, 1, 5, 6, 10, 50, 60
- **Connectivity:** PCIe 5.0 x8
1.5. Networking and I/O
High-speed networking is essential for clustered environments and distributed computing. The configuration leverages OCP 3.0 form factor for flexible, high-throughput adapters.
| Port Type | Quantity | Speed | Interface Standard | Location |
|---|---|---|---|---|
| Onboard Management | 2x 1GbE (Dedicated) | 1 Gbps | RJ-45 | Rear Panel |
| Primary Data Fabric (OCP 3.0) | 2x 100GbE | 100 Gbps | QSFP28 (or future QSFP-DD) | OCP Slot 1 |
| Secondary Fabric (PCIe Slot) | 1x 200GbE InfiniBand EDR/HDR | 200 Gbps | Mellanox ConnectX-7 Equivalent | PCIe 5.0 x16 Slot |
The system supports RDMA (Remote Direct Memory Access) over Converged Ethernet (RoCE) and InfiniBand for low-latency inter-server communication, vital for HPC workloads.
1.6. Graphics Processing Units (Optional/Expansion)
While primarily a CPU-bound system, the HDCN-8000 supports accelerator cards via its dedicated PCIe slots.
- **Maximum Supported GPUs:** 4x Full-Height, Dual-Slot Accelerator Cards (e.g., NVIDIA H100 SXM5 equivalent, requiring specific power provisioning).
- **Power Budget:** The chassis supports up to 4000W total system power, allowing for high-TDP accelerators provided the primary CPUs are configured with lower TDP profiles (e.g., 250W). GPU Computing integration is managed via PCIe Bifurcation and dedicated power rails.
2. Performance Characteristics
The performance evaluation of the HDCN-8000 focuses on its ability to handle massive parallel tasks, high transaction rates, and demanding memory throughput benchmarks.
2.1. Synthetic Benchmarks
Benchmarks are executed using standardized testing methodologies on a fully populated, optimally configured system (2TB DDR5, 240 Threads, NVMe RAID 0 array).
2.1.1. CPU Throughput (SPECrate 2017 Integer)
This metric assesses the system's ability to execute complex, real-world integer workloads across all available cores.
| Metric | HDCN-8000 Result (Score) | Comparison Baseline (Previous Gen 2U System) |
|---|---|---|
| SPECrate 2017 Integer | > 18,500 | ~12,000 |
| Single-Thread Performance Index | 4.1 (Normalized to 1.0 baseline) | 2.8 |
The significant increase is attributed to the higher core count (120 vs 80) and the substantial IPC (Instructions Per Cycle) uplift of the new microarchitecture.
2.1.2. Memory Bandwidth and Latency
Memory performance is measured using STREAM benchmarks, focusing on the aggregate bandwidth across all 16 channels.
| Test | Result (GB/s) | Notes |
|---|---|---|
| STREAM Triad Bandwidth (Aggregate) | > 1150 GB/s | Achieves near-theoretical maximum for 4800 MT/s DDR5 across 16 channels. |
| Random Read Latency (tCL) | ~65 ns | Optimized BIOS settings for latency reduction. |
This bandwidth is essential for memory-bound applications such as large-scale In-Memory Databases and scientific simulations.
2.1.3. Storage I/O Performance
Measured using FIO (Flexible I/O Tester) against the 8x NVMe array configured in RAID 0.
| Workload Type | Configuration | Result |
|---|---|---|
| Sequential Read Throughput | 128K Block Size | > 35 GB/s |
| Random Read IOPS (4K Blocks) | 100% Read, QD32 | > 4.5 Million IOPS |
| Random Write IOPS (4K Blocks) | 100% Write, QD32 | > 3.1 Million IOPS |
The performance ceiling is determined by the PCIe 5.0 lanes (x32 total available to the storage subsystem) and the efficiency of the RAID controller.
2.2. Real-World Application Performance
Performance is contextualized using industry-standard application benchmarks.
2.2.1. Virtualization Density (VMware vSphere)
The system is tested for its capacity to host virtual machines (VMs) running standard enterprise workloads (mix of web servers, application servers, and VDI).
- **Test Metric:** Maximum sustained VM count before performance degradation (defined as >5% additional latency on average VM response time).
- **Result:** 280 Standard x86-64 VMs (each provisioned with 4 vCPUs, 8 GB RAM).
- **Key Factor:** The 120 physical cores and 2TB RAM allow for high consolidation ratios while maintaining reasonable S-rates (Service Rates) for each VM.
2.2.2. Database Transaction Processing (TPC-C)
A critical benchmark for OLTP workloads.
- **Configuration:** 1 TB PostgreSQL database instance residing on the NVMe array.
- **Result:** 1.9 Million Transactions Per Minute (tpmC).
- **Analysis:** The strong single-thread performance (high turbo boost) combined with the high core count for concurrent connection handling yields excellent TPC-C scores, demonstrating robust OLTP capabilities. This is superior to configurations relying heavily on AMD EPYC architectures when I/O latency spikes are a primary concern.
2.2.3. Container Orchestration (Kubernetes)
Measured by the time taken to deploy and stabilize a predefined complex microservices application stack (150 containers).
- **Deployment Time:** 4 minutes, 12 seconds.
- **Resource Utilization:** Sustained CPU utilization across the cluster averaged 65% during the stabilization phase.
- **Networking Impact:** The 100GbE fabric minimized inter-service latency (average pod-to-pod latency < 15 microseconds), which is crucial for distributed transaction integrity.
3. Recommended Use Cases
The HDCN-8000 is engineered for environments where compute density, high memory capacity, and fast internal communication are paramount. It is not optimized for graphics-intensive rendering or low-core-count, very high-frequency legacy applications.
3.1. High-Performance Computing (HPC) Clusters
The combination of high core density, massive RAM capacity, and low-latency interconnects (via InfiniBand/RoCE) makes this ideal for scientific modeling.
- **Fluid Dynamics Simulations (CFD):** Workloads that scale well across hundreds of cores benefit immensely from the 120-core configuration.
- **Molecular Dynamics:** Requires high memory bandwidth to move large datasets between processing units efficiently.
- **Weather Modeling:** The platform's ability to handle large MPI (Message Passing Interface) jobs is maximized by the fast interconnects.
3.2. Large-Scale Virtual Desktop Infrastructure (VDI)
The system excels as a VDI host due to its ability to support a large number of users per physical server while maintaining acceptable user experience metrics (UXM).
- **Density:** Supports up to 300 concurrent knowledge workers or 150 power users.
- **Requirement Fulfillment:** The ample local NVMe storage ensures fast boot times and rapid application loading for individual desktops.
3.3. Enterprise Data Warehousing and In-Memory Analytics
For systems requiring the entire analytical dataset to reside in volatile memory for real-time querying.
- **SAP HANA:** This configuration meets the strict I/O and memory capacity requirements for Tier-1 SAP HANA deployments, particularly those utilizing the 2TB memory ceiling.
- **Business Intelligence (BI) Servers:** Hosting large analytical cubes (e.g., using Microsoft SQL Server Analysis Services or equivalent) where query response time depends on eliminating disk access latency.
3.4. Cloud and Hyperscale Infrastructure
Used as a foundation for private or public cloud environments requiring dense virtual machine hosting or container platforms.
- **Container Host Density:** Maximizing the number of pods/containers per physical host to reduce infrastructure overhead costs.
- **Database as a Service (DBaaS):** Hosting high-throughput relational or NoSQL databases where the 2TB RAM can serve as a massive read/write buffer pool.
4. Comparison with Similar Configurations
To contextualize the HDCN-8000, we compare it against two common alternatives: a high-core-count AMD EPYC system (focused on core count parity) and a dense GPU accelerator node (focused on heterogeneous computing).
4.1. Configuration Comparison Table
| Feature | HDCN-8000 (Intel Dual-Socket) | AMD EPYC 9004 Series (Dual-Socket) | GPU Accelerator Node (Dual-Socket) |
|---|---|---|---|
| Total Physical Cores | 120 | 128 (Example: 2x 64C) | 64 (CPU Cores) |
| Max DDR5 Channels | 16 | 24 | |
| Max System RAM | 2 TB (Current Config) / 8 TB (Max) | 12 TB (Theoretical Max) | 1 TB (CPU RAM) + 192 GB (HBM on GPUs) |
| PCIe Lanes (Total) | 112 (Gen 5.0) | 160 (Gen 5.0) | |
| Primary Strength | Balanced I/O, Strong Single-Thread IPC, QAT Acceleration | Maximum Core Count, Memory Bandwidth Scalability | Raw Floating Point Compute (FP64/FP16) |
| Ideal Workload | Virtualization, OLTP, Enterprise Databases | Large Memory HPC, High-Density VM Hosting | AI Training, Deep Learning Inference, Scientific Simulation (GPU-bound) |
4.2. Architectural Trade-offs Analysis
- 4.2.1. Core Count vs. IPC
While the AMD EPYC configuration offers a higher maximum core count (128 vs. 120), the HDCN-8000 leverages superior Instructions Per Cycle (IPC) performance and higher sustained clock speeds under heavy load (due to optimized thermal design for 350W TDP CPUs). For latency-sensitive applications, the HDCN-8000 often provides a lower execution time despite having fewer total cores. This is critical in Latency Sensitive Computing.
- 4.2.2. Memory Subsystem
The 16-channel memory architecture of the HDCN-8000 provides substantial bandwidth suitable for its 120 cores. However, the theoretical advantage lies with the 24-channel EPYC platform, which can reach significantly higher aggregate bandwidth (potentially >1.5 TB/s). System architects must weigh the cost of populating 24 DIMM slots versus the performance gain for their specific workload.
- 4.2.3. I/O Density and Expansion
The HDCN-8000 is optimized for utilizing PCIe Gen 5.0 for storage (NVMe) and networking (100GbE), offering excellent throughput for I/O-heavy tasks without immediately requiring dedicated accelerators. The GPU Node sacrifices general-purpose I/O lanes for direct high-speed connectivity to the accelerator fabric (e.g., NVLink or CXL).
5. Maintenance Considerations
Proper maintenance is vital for ensuring the high availability and sustained performance of the HDCN-8000, particularly given its high component density and thermal output.
5.1. Power Requirements and Management
The dual 2000W PSUs provide substantial headroom, but careful power planning is necessary for rack density.
- **Peak Power Draw:** Under full load (CPUs maxed, all NVMe drives active, 100GbE saturated), the system can draw up to 1850W (excluding optional high-TDP GPUs).
- **PDU Requirements:** Each rack unit housing the HDCN-8000 should be provisioned with at least 2.5 kW capacity per PDU outlet to handle inrush current and sustained load safely.
- **Power Monitoring:** Utilize the BMC’s power monitoring features to track Power Usage Effectiveness (PUE) at the server level. Monitoring Voltage Regulation Modules (VRMs) is crucial for detecting early signs of component degradation.
5.2. Thermal Management and Airflow
The 2U chassis design channels significant heat, demanding high-quality rack cooling infrastructure.
- **Ambient Temperature:** Maximum recommended ambient temperature for inlet air is 25°C (77°F). Exceeding this threshold will force the BMC to throttle CPU frequency to maintain junction temperatures below 95°C, directly impacting performance metrics detailed in Section 2.
- **Fan Redundancy:** The N+1 fan configuration ensures that a single fan failure does not cause immediate thermal shutdown. Regular physical inspection of fan health status via the Redfish API is recommended monthly.
- **Airflow Obstruction:** Ensure no external cabling obstructs the front-to-rear airflow path. Hot-swappable components must be replaced immediately to maintain the system's thermal envelope integrity.
5.3. Component Serviceability
The design emphasizes serviceability for rapid component replacement, minimizing Mean Time To Repair (MTTR).
- **Hot-Swappable Components:** PSUs, Fans, and all 20 Storage Drives (NVMe/SAS) are hot-swappable.
- **CPU/RAM Replacement:** Requires opening the top cover and removing the air shroud. Due to the high density of DIMMs, careful handling and adherence to Electrostatic Discharge (ESD) protocols are mandatory during memory upgrades.
- **Firmware Updates:** The Baseboard Management Controller (BMC) must be kept current. Critical firmware updates often include microcode patches addressing security vulnerabilities (e.g., Spectre/Meltdown mitigations) and performance stability fixes for the integrated I/O Controller Hub (ICH). Scheduled maintenance windows must allocate time for firmware and BIOS updates, particularly following major OS kernel releases.
5.4. Storage Health Monitoring
Proactive monitoring of the storage subsystem prevents data loss and performance degradation.
- **NVMe Telemetry:** Monitor SMART data and NVMe-specific health logs (e.g., Media Errors, Temperature) for the 8x primary drives. Given their high IOPS usage, drive endurance (TBW) should be tracked against warranty limits.
- **RAID Controller Health:** Regularly check the status of the write cache battery/capacitor (FBWC) on the RAID controller. A failed backup unit can lead to data loss during a power event, even with redundant PSUs.
- **Disk Scrubbing:** Implement automated, monthly full-disk scrubbing routines on the SAS/SATA array to detect and repair latent sector errors, maintaining data integrity in the bulk storage tier.
5.5. Network Interface Health
High-speed interconnects require specific attention beyond standard diagnostics.
- **Error Counters:** Monitor input/output error counters on the 100GbE and 200GbE ports for CRC errors, dropped packets, and link training failures. High error rates usually indicate a faulty QSFP transceiver, defective DAC/fiber cable, or an issue with the upstream switch port.
- **RDMA Verification:** For HPC applications using RDMA, periodic link diagnostics (e.g., using vendor-specific tools) must confirm low latency path integrity, as minor physical layer issues can drastically increase communication overhead.
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️